Posted today · be early

Senior Data Scientist with NLP

Stermedia

WorldwideremotePosted 1 day ago

Skill Required

Data-ScientistMachine-Learning-EngineerNLP-EngineerAI-EngineerNLP-Data-ScientistSenior-Machine-Learning-Data-ScientistNLP-Research-ScientistSenior-AI-ML-ScientistSenior-Machine-Learning-ScientistSenior-Data-ScienceData ScientistNLPSystem DesignGenerative AIBusiness AnalysisMachine LearningDeep LearningObservabilityKubernetesEngineeringR ProgrammingTensorFlowautomationLangChainPyTorchsecuritybuildingXGBoostMLflowetc.)TestNGAzurePythonDockerdesignDevOpsFulltime

Key highlights

Salary: 20 000 - 30 000 PLN + VAT (B2B)
Required: Proficiency in Python and GenAI/LLM frameworks
Benefit: Budget for self-development per year
Benefit: Remote work possibility

Role overview

You’ll be working on diverse machine learning projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery – direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment.

Responsibilities

Design and develop end-to-end agentic AI solutions using modern LLM frameworks
Build and deploy Generative AI applications using Python
Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows
Implement agent orchestration for multi-agent systems and complex task automation
Apply advanced prompt engineering techniques to optimize model performance
Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails)
Deploy AI solutions using container-based architectures (Docker, Kubernetes)
Ensure scalability, reliability, and security of AI systems in production
Integrate AI agents with enterprise APIs, databases, and external systems
Continuously evaluate model performance and implement optimization strategies

Requirements

Strong proficiency in Python programming
Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, etc.)
Experience building end-to-end agentic solutions
Practical experience in agent development and orchestration
Expertise in prompt engineering and LLM optimization
Experience with container-based deployments (Docker, Kubernetes)
Experience implementing agent observability (monitoring, tracing, evaluation frameworks)
Knowledge of REST APIs and backend integration patterns
Experience deploying AI applications in cloud environments (AWS / Azure / GCP)
Understanding of RAG architectures, embeddings, vector databases

Nice to have

Experience with multi-agent collaboration frameworks
Experience with evaluation tools (e.g., prompt testing, hallucination detection, guardrails)
Familiarity with MLOps practices
Knowledge of distributed systems design
Experience with real-time AI applications
Background in machine learning fundamentals
Communicative English – minimum C1 level
Experience with DevOps / MLOps tools and practices (e.g. Docker, Kubernetes, MLFlow, KubeFlow, DVC)
Familiarity with a deep learning framework (Tensorflow, PyTorch)
Experience in using additional data science related libraries (e.g. nltk, opencv, scikit-image, gensim, plotly, seaborn, xgboost, lightgbm)
Strong general software development skills and knowledge of best practices
Algorithmic and code optimization skills
Knowledge of a cloud platform and experience in running cloud-based projects (GCP, AWS, Azure)